Training on Supply Chain Digital Twins and Simulation Modeling

Module 1: Introduction to Digital Twins and Simulation

• Defining digital twin: static vs. dynamic, descriptive vs. predictive.

• The value of simulation in supply chain decision-making.

• Types of simulation: discrete event, agent-based, and system dynamics.

• Case Study/Hands-on Exercise: Analyze a case where simulation was used to redesign a distribution network, quantifying the cost savings and risk reduction achieved.

Module 2: Simulation Modeling Fundamentals

• Key concepts: entities, resources, processes, and queues.

• Input data requirements: distributions, variability, and uncertainty.

• Model building blocks and logic structures.

• Case Study/Hands-on Exercise: Map the process flow for a warehouse receiving operation, identifying entities, resources, and decision points to prepare for simulation modeling.

Module 3: Data Collection and Input Analysis

• Collecting and cleaning operational data for simulation.

• Fitting statistical distributions to real-world data (e.g., arrival rates, processing times).

• Validating input data assumptions.

• Case Study/Hands-on Exercise: Analyze a dataset of truck arrival times at a distribution center, fit a probability distribution, and test the goodness of fit.

Module 4: Building a Digital Twin of a Distribution Center

• Modeling warehouse processes: receiving, putaway, picking, packing, and shipping.

• Representing resources: labor, equipment, and storage locations.

• Incorporating shift schedules and resource constraints.

• Case Study/Hands-on Exercise: Build a basic discrete event simulation model of a warehouse pick-and-pack operation, defining process steps, resources, and entity flow.

Module 5: Network Digital Twins and Optimization

• Modeling the flow of goods across a multi-echelon network.

• Integrating transportation modes, lead times, and costs.

• Using digital twins for inventory optimization and service level analysis.

• Case Study/Hands-on Exercise: Create a network digital twin for a company with three distribution centers and 50 customer zones, simulating inventory policies and transportation costs.

Module 6: Scenario Analysis and What-If Testing

• Designing experiments to test scenarios: demand spikes, supplier disruptions, labor shortages.

• Comparing baseline vs. alternative scenarios.

• Sensitivity analysis to identify critical variables.

• Case Study/Hands-on Exercise: Using a network digital twin, simulate the impact of a 30% demand surge on service levels and transportation costs, and test mitigation strategies.

Module 7: Simulation for Automation and Technology Decisions

• Modeling the impact of automation: robotics, conveyors, and AS/RS.

• Comparing manual vs. automated scenarios.

• Estimating ROI and throughput improvements.

• Case Study/Hands-on Exercise: Build a simulation comparing a manual picking zone to a goods-to-person robotics zone, quantifying throughput, labor requirements, and cycle time improvements.

Module 8: Model Validation and Verification

• Ensuring the model accurately represents the real system.

• Verification techniques: debugging, logic checking, and animation review.

• Validation techniques: comparing model outputs to historical data.

• Case Study/Hands-on Exercise: Compare simulation output data for a warehouse model with historical actual data, identify discrepancies, and refine the model to improve accuracy.

Module 9: Advanced Simulation Techniques

• Integrating simulation with optimization algorithms.

• Using simulation for supply chain risk analysis and stress testing.

• Agent-based modeling for complex supply chain behaviors.

• Case Study/Hands-on Exercise: Apply simulation-based optimization to determine the optimal safety stock levels for a network, balancing inventory cost against service level risk.

Module 10: Implementing Simulation Insights and Building Capability

• Communicating simulation results to stakeholders.

• Embedding simulation into strategic planning cycles.

• Building internal simulation capabilities and centers of excellence.

• Case Study/Hands-on Exercise: Prepare a presentation summarizing simulation findings for a network redesign project, including recommendations, expected benefits, and implementation considerations.